Model routing strategy
In plain wordsUsing your most expensive model for everything is like sending every letter by courier. We help you write the rules for which model does which job.
Croutons evaluates model routing and provider/fallback strategy so task class, risk and measured quality drive assignment, not ad hoc overrides.
The problem
Multiple models serve the same workflows without consistent routing rules, causing quality drift, wasted capacity and opaque fallbacks.
Signs you have it
- Manual model overrides in production
- Inconsistent answers across similar tasks
- Fallback to frontier models under any error
- No documented provider failover policy
Who it is for
Platform teams managing model gateways and agent orchestration.
What we look at
- Task class versus model capability
- Risk tier and approval needs
- Latency and cost targets
- Provider and fallback behavior under failure
What to send us
- Current routing tables or gateway config
- Model inventory and pricing
- Failure and override logs
- Quality or eval samples by class
How the diagnosis works
Derive routing rules from task class, risk and measured fit. Document provider and fallback strategy as part of routing, not as an afterthought. Propose pilots before broad cutover.
What you get
- Routing policy draft by task class
- Fallback and provider strategy notes
- Override reduction recommendations
- Pilot and measurement plan
Expected outcome
Predictable model assignment with explicit trade-offs and fewer opaque overrides.
Limits, stated up front
- Does not replace your gateway product
- Quality labels bound routing confidence
- Provider outages still require operational runbooks
Related use cases
Inference cost diagnosis
Your AI bill keeps growing. We show you which models, agents and retries are driving it, and what to change first.
Cost–latency–quality optimization
Cheaper, faster and better pull against each other. We help you decide the trade-off per job instead of guessing.
Agent reliability analysis
Your AI agent gives different answers, retries too much or fails without telling anyone. We find out why and what to fix first.
Model routing strategy: common questions
What is model routing in simple terms?
A set of rules that decides which AI model handles each request, based on how hard the job is, how risky a mistake would be, and how fast and cheap it needs to be.
We already have an AI gateway. Do we still need this?
A gateway executes routing rules; it does not tell you what the rules should be. The diagnosis gives you rules backed by task class, risk and measured quality to load into the gateway you already run.
What happens when a model provider goes down?
That is part of the routing policy. We document which fallback each task class should use, and when a fallback should stop instead of silently escalating to the most expensive model.
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